Mapping the Infant Brain Developmental Connectome: Temporally Precise Growth Trajectories of Changing Infant Brain Topology

绘制婴儿大脑发育连接组图：改变婴儿大脑拓扑的时间精确生长轨迹

• 批准号: 9973737
• 负责人: Longchuan Li
• 金额: $ 27.43万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-07 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9973737
• 关键词: Address; Adopted; Anatomy; Area; Behavioral; Benchmarking; Birth; Brain; Brain region; Communities; Complex; Data; Data Set; Dependence; Development; Developmental Process; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Event; Four-dimensional; Functional Magnetic Resonance Imaging; Future; Goals; Graph; Growth; Head; Human; Infant; Infant Behavior; Knowledge; Lead; Learning; Life; Link; Maps; Measures; Modernization; Neurodevelopmental Disability; Neurodevelopmental Disorder; Neurosciences; Nodal; Pathway Analysis; Pathway interactions; Pattern; Process; Research; Rest; Sampling; Science; Scientific Inquiry; Site; Structure; Synapses; System; Techniques; Time; brain behavior; brain volume; cognitive development; cognitive function; connectome; curve fitting; density; design; disability; environmental change; flexibility; graph theory; infancy; insight; longitudinal design; neurophysiology; novel; postnatal; response; spatiotemporal; success

PROJECT SUMMARY/ABSTRACT The overarching goal of this proposal is to advance our knowledge of early brain development by mapping temporally precise developmental trajectories of brain network topology and dynamics during the first 6 months of life, a period of unparalleled postnatal growth and change. Describing the developmental trajectory of brain systems during this formative period has the potential to provide groundbreaking insights into major areas of scientific inquiry, including the identification of brain systems that underlie the development of cognitive functions, the discovery of how structural and functional network specializations arise, and the identification of brain networks that contribute to neurodevelopmental disability. Using a novel non-uniform longitudinal sampling design and advanced non-parametric curve fitting techniques, the proposed project will map four- dimensional, temporally accurate developmental trajectories of brain structural and functional networks in typically developing infants between birth and the 6th month of life (Aim 1). These connectomes will be made publicly available to the research community. In Aim 2, the latest advances in dynamic network science will be applied to identify community structure (i.e., modules of densely inter-connected brain regions) in time-varying infant brain networks. Finally, fine scale changes in the community dynamics of infant brain networks will be characterized to understand how modules and their interactions change over developmental time (Aim 3). Analyses will be conducted on anatomical, diffusion, and resting-state functional MRI data collected from infants at non-uniform, densely sampled time points between birth and 6 months. The success of the project will significantly advance our understanding of the dynamic processes of brain network development in early infancy, a pivotal, and yet relatively uncharted, period of development.

项目概要/摘要 该提案的总体目标是通过绘制地图来增进我们对早期大脑发育的了解 前 6 个月内大脑网络拓扑和动力学的时间精确发展轨迹 生命的一段时期，是出生后无与伦比的成长和变化的时期。描述大脑的发育轨迹 在此形成时期的系统有潜力为主要领域提供突破性的见解 科学探究，包括识别认知发展背后的大脑系统 功能，发现结构和功能网络专业化如何产生，以及识别 导致神经发育障碍的大脑网络。使用新颖的非均匀纵向 抽样设计和先进的非参数曲线拟合技术，拟议的项目将绘制四个 大脑结构和功能网络的维度、时间精确的发育轨迹 通常是在出生到第 6 个月之间发育的婴儿（目标 1）。这些连接体将被制成 向研究界公开提供。在目标 2 中，动态网络科学的最新进展将是 用于识别随时间变化的群落结构（即密集互连的大脑区域的模块） 婴儿大脑网络。最后，婴儿大脑网络群落动态的精细尺度变化将是 旨在了解模块及其交互如何随开发时间而变化（目标 3）。 将对从收集的解剖、扩散和静息态功能 MRI 数据进行分析 婴儿出生至 6 个月期间的不均匀、密集采样时间点。项目的成功 将显着促进我们对早期大脑网络发育动态过程的理解 婴儿期是一个关键但相对未知的发展时期。